Laser speckle contrast imaging (LSCI) is a non-scanning, wide-field technique useful in visualizing blood vessels and blood flow without the introduction of any exogenous contrast agents. It has been widely used in neuroscience research. Incidence of coherent illumination on living tissue gives rise to interference patterns called speckles. When this speckle pattern is photographed, the movement of red blood cells within blood vessels causes a blurring effect over the exposure time of the imaging camera. Such a blur can be quantified in terms of a quantity called laser speckle contrast (K) at each pixel P0(x0,y0,n0) using:
      K    ⁡          (              P        0            )        =            σ              N        ⁡                  (                      P            0                    )                            μ              N        ⁡                  (                      P            0                    )                    Where σN(P0) and μN(P0) are the standard deviation and mean respectively of the intensities of all pixels in a defined local neighborhood N(P0) of P0; and (x0,y0,n0) denote the location of the pixel in the spatial (x-y) plane of the image and the number of the sequentially acquired image frame n. Traditionally, N is chosen in either exclusively the spatial domain (called sLSCI herein) or exclusively the temporal domain (called tLSCI herein). tLSCI optimizes spatial resolution by compromising temporal resolution, while sLSCI optimizes temporal resolution by compromising the spatial resolution.
Because traditional speckle contrast processing schemes use pixel neighborhoods that are isotropic in the spatial domain, often a square of pixels, accurate representation of blood velocity is confounded. This is because blood velocity changes steeply along the diameter of the vessel. However, blood flow within blood vessels with diameters less than approximately 200 micrometers is orderly and aligned along the axial direction of these vessels. The axial direction for a vessel is clarified as the direction parallel to the centerline and perpendicular to the diameter of the vessel in consideration. Further, the change in blood velocities along the axial direction is minimal. Thus, speckle blurring is expected to show directional sensitivity, allowing for preferential processing of speckle data along the direction of blood flow thereby preventing the loss of spatial resolution or any radial confounding of the signal. Further, this allows for reducing the size of the neighborhood in the temporal domain, while still retaining enough pixels in the neighborhood to obtain reliable estimation of the local K values, thereby significantly improving the temporal resolution. Techniques have previously been reported that utilize isotropic approaches to address the issue of spatiotemporal resolution. Temporally averaged spatial speckle contrast calculation, (called tavgsLSCI herein) and spatially averaged temporal speckle contrast calculation, (called savgtLSCI herein) achieve robustness by smoothing sLSCI and tLSCI images in the temporal and spatial domains respectively. Three dimensional spatiotemporal processing, (called stLSCI herein) uses a cuboid of pixels in the spatiotemporal domain as the neighborhood in which local K values are calculated.
It would therefore be advantageous to provide a system and method that can achieve both high spatial resolution as well as high temporal resolution, so that rapid flow changes could be monitored at the level of microvessels or conversely the image acquisition time be commensurately reduced. It would also be advantageous to provide a system and method to calculate local speckle contrast along an estimated direction of blood flow at each pixel, while using a few frames along the temporal dimension, thus keeping the window two-dimensional in the spatiotemporal domain.